October 17, 2005ICP: Chapter 5: Lists and Dictionaries 1 Introduction to Computer Programming...

October 17, 2005 ICP: Chapter 5: Lists and Dictionaries

1

Introduction to Computer Programming

Chapter 5: Lists and Dictionaries

Michael Scherger

Department of Computer Science

Kent State University


2

Contents

• Using Lists

• List Methods

• Tuples vs Lists

• Nested Sequences

• Shared References

• Using Dictionaries

• Hangman Game


3

Hangman

• Example: Hangman

http://www.cs.kent.edu/~mscherge/ICP/PythonBookExamples/chap05/hangman.py


4

Introduction

• Data structures– Structures that hold and organize information

• Sequences– Also know as arrays in other languages– Store related data types– 3 types

• Strings• Lists• Tuples

• Mappings– In most languages called hashes or associative arrays– Dictionaries are the only python mapping container


5

Hero’s Inventory 3.0 Program

• Example: Hero’s Inventory 3.0

http://www.cs.kent.edu/~mscherge/ICP/PythonBookExamples/chap05/hero's_inventory3.py


6

Creating Sequences (Review)• Strings

– Use quotes– string1 = ""

• Tuples– Use parenthesis– Separate multiple items with a comma– tuple = ()– singleton = 1, - this is a one element tuple or a singleton

• Lists– Use brackets– Separate multiple items with a comma– list1 = []


7

Using Lists

• Creating a Listanylist = []chevycars = [“Corvette”, “Aveo”, “Malibu”, “Cobalt”, “Impala”, “Silverado”, “Trailblazer”, “Tahoe”, “Colorado”, “Suburban”]

• Length Functionnum_cars = len( chevycars )

• in Operatorif “Corvette” in chevycars:print “That’s a nice car!!!!”


8

Using Lists

• Indexingprint chevycars[4]

• Slicingprint chevycars[0:4]

• Concatenationchevycars += [ “SSR”, “Monte Carlo”, “Avalanche”, “Equinox”, “Blazer”, “Astro”, “Uplander”, “Venture” ]


9

Using Lists

• Lists are mutable – The elements in a list can change value

• Change by assignmentxmaslist[0] = “Black Corvette with optional blonde”

xmaslist[1] = “Trip to Las Vegas”

• Change by slicinginventory[4:6] = “Orb of Future Telling”


10

Using Lists

• Deleting a list elementdel inventory[2]

• Deleting a list slicedel inventory[4:6]


11

List Methods

• append(value)– Adds value to the end of the list

• sort()– Sorts the elements, smallest value first

• reverse()– Reverses the order of a list

• count(value)– Returns the number of occurences of value in the list


12

List Methods

• index(value)– Returns the first position number of where value occurs

• insert(i, value)– inserts value at position i

• pop([i])– Returns value at position i and removes value from the list.

Providing the position number is optional. Without it, the last element in the list is removed.

• remove(value)– Removes the first occurrence of value from the list.


13

List Methods

• Example: High Scores Program

http://www.cs.kent.edu/~mscherge/ICP/PythonBookExamples/chap05/high_scores.py


14

Tuples vs. Lists

• Tuples are faster than lists. Because the computer knows they will not change, tuples can be stored in a way that makes using them faster that using lists. For simple programs, this speed difference will not matter, but in more complex applications, with very large sequences of information, it could.

• Tuples’ immutability makes them perfect for creating constants since they cannot change. Using tuples can add a level of safety and clarity to your code.

• Sometimes tuples are required. In some cases Python requires immutable values. (Example shown later when Dictionaries are discussed.)


15

Nested Sequences

• Tuples and Lists can be sequences of anything– Including other tuples and lists

• Nested Sequences– Sequences inside other sequences– A great method to organize complex collections of

information

• Common use is a table– By convention it is organized by row and column


16

Nested Sequences

Row 0

Row 1

Row 2

Column 1Column 0 Column 2 Column 3

a[0][0] a[0][3]a[0][1] a[0][2]

a[1][0] a[1][3]a[1][1] a[1][2]

a[2][0] a[2][3] a[2][2]

Column index (or subscript)

Row index (or subscript)

Array name

a[2][1]


17

Nested Sequences

• Creating nested sequences (examples)

nested_1 = [“first”, (“second”, “third”), [“fourth”, “fifth”, “sixth” ]]

scores = [(“Moe”, 1000),(“Larry”, 1500),(“Curly”, 2000)]

nested_2 = (“deep”,(“deeper”,(“deepest”,”still deepest”)))


18

Nested Sequences

• Accessing Nested Sequences (example)>>> scores = [(“Moe”, 1000),(“Larry”, 1500),(“Curly”, 2000)]>>> print scores[0](‘Moe’, 1000)>>> print scores[1](‘Larry’, 1500)>>> print scores[2](‘Curly’, 2000)

>>> a_score = scores[2]>>> print a_score(‘Curly’, 2000)>>> print a_score[0]Curly

>>> print scores[2][0]Curly>>> print scores[2][0][4]y


19

Nested Sequences1. table1 = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ]2. table2 = ( ( 1, 2 ), ( 3, ), ( 4, 5, 6 ) )3. 4. print "Values in table1 by row are"5. 6. for row in table1:7. 8. for item in row:9. print item,10. 11. print12. 13. print "\nValues in table2 by row are"14. 15. for row in table2:16. 17. for item in row:18. print item,19. 20. print

Values in table1 by row are1 2 34 5 6

Values in table2 by row are1 234 5 6

This list has two rows

This tuple has three rows

A nested for loop is needed to display all of the items in the list


20

Nested Sequences Example

• Example: High Scores 2.0 Program

http://www.cs.kent.edu/~mscherge/ICP/PythonBookExamples/chap05/high_scores2.py


21

Shared References• Consider the following

example…s = “Python”

• The variable s refers to a place in memory where the string value “Python” is stored.

• A variable refers to a value the same way a person’s name refers to a person. It would be wrong to say that a person’s name “stores” the person. Using a person’s name you can get to the person. Using a variable’s name you can get to a value.

“Python

s

• For lists, when several variables refer to the same mutable value, they share the same reference!


22

Shared References>>> mike = ['khakis', 'dress shirt', 'jacket']>>> mr_scherger = mike>>> honey = mike>>> print mike['khakis', 'dress shirt', 'jacket']>>> print mr_scherger['khakis', 'dress shirt', 'jacket']>>> print honey['khakis', 'dress shirt', 'jacket']>>>


23

Shared References

“khakis” “dress shirt” “jacket”

mike

mr_scherger

honey


24

Shared References>>> mike = ['khakis', 'dress shirt', 'jacket']>>> mr_scherger = mike>>> honey = mike>>> print mike['khakis', 'dress shirt', 'jacket']>>> print mr_scherger['khakis', 'dress shirt', 'jacket']>>> print honey['khakis', 'dress shirt', 'jacket']>>> >>> >>> honey.append('brown shoes')>>> print mike['khakis', 'dress shirt', 'jacket', 'brown shoes']>>>


25

Dictionaries

• Programmers love to organize information– Lists and tuples organize things into

sequences

• Dictionaries stores information in pairs– Similar to an actual dictionary

• Word and definition• Python uses key and value


26

Dictionaries

• Example: Geek Translator

http://www.cs.kent.edu/~mscherge/ICP/PythonBookExamples/chap05/geek_translator.py


27

Dictionaries

• Dictionaries– Mapping constructs consisting of key-value

pairs• Referred to as hashes in other languages

– Unordered collection of references– Each value is referenced though key in the

pair


28

Dictionaries

– Curley braces ({}) are used to create a dictionary

– When entering values• Use { key1:value1, … }

– Keys must be immutable values such as strings, numbers and tuples

– Values can be of any Python data type


29

Dictionaries# create and print an empty dictionaryemptyDictionary = {}print "The value of emptyDictionary is:", emptyDictionary # create and print a dictionary with initial valuesgrades = { "John": 87, "Steve": 76, "Laura": 92, "Edwin": 89 }print "\nAll grades:", grades # access and modify an existing dictionaryprint "\nSteve's current grade:", grades[ "Steve" ]grades[ "Steve" ] = 90print "Steve's new grade:", grades[ "Steve" ] # add to an existing dictionarygrades[ "Michael" ] = 93print "\nDictionary grades after modification:"print grades # delete entry from dictionarydel grades[ "John" ]print "\nDictionary grades after deletion:"print grades

Alters and displays the new grade for Steve

Creates an empty dictionary

Adds a new name to the grades dictionary

Removes the name john from the dictionary with the del keyword

Creates a grades dictionary using names as the key and their grade as the value


30

DictionariesThe value of emptyDictionary is: {} All grades: {'Edwin': 89, 'John': 87, 'Steve': 76, 'Laura': 92} Steve's current grade: 76Steve's new grade: 90 Dictionary grades after modification:{'Edwin': 89, 'Michael': 93, 'John': 87, 'Steve': 90, 'Laura': 92} Dictionary grades after deletion:{'Edwin': 89, 'Michael': 93, 'Steve': 90, 'Laura': 92}


31

Dictionaries

Method Description

clear() Deletes all items from the dictionary.

copy() Creates and returns a shallow copy of the dictionary (the elements in the new dictionary are references to the elements in the original dictionary).

get( key [, returnValue] ) Returns the value associated with key. If key is not in the

dictionary and if returnValue is specified, returns

the specified value. If returnValue is not specified,

returns None.

has_key( key ) Returns 1 if key is in the dictionary; returns 0 if key is

not in the dictionary.

items() Returns a list of tuples that are key-value pairs.

keys() Returns a list of keys in the dictionary.

popitem() Removes and returns an arbitrary key-value pair as a tuple of two elements. If dictionary is empty, a Key-Error exception occurs. [Note: We discuss

exceptions in Chapter 12, Exception Handling.] This method is useful for accessing an element (i.e., print the key-value pair) before removing it from the dictionary.


32

Dictionaries

setdefault( key [, dummyValue] )

Behaves similarly to method get. If key is not in the dictionary and dummyValue is specified, inserts the key and the specified value into dictionary. If

dummyValue is not specified, value is None.

update( newDictionary ) Adds all key-value pairs from newDictionary to the current dictionary and overrides the values for keys that already exist.

values() Returns a list of values in the dictionary.


33

Dictionaries>>> dictionary = { "listKey" : [ 1, 2, 3 ] }>>> shallowCopy = dictionary.copy() # make a shallow copy>>> dictionary[ "listKey" ].append( 4 )>>> print dictionary{'listKey': [1, 2, 3, 4]}>>> print shallowCopy{'listKey': [1, 2, 3, 4]} >>> from copy import deepcopy>>> deepCopy = deepcopy( dictionary ) # make a deep copy>>> dictionary[ "listKey" ].append( 5 )>>> print dictionary{'listKey': [1, 2, 3, 4, 5]}>>> print shallowCopy{'listKey': [1, 2, 3, 4, 5]}>>> print deepCopy{'listKey': [1, 2, 3, 4]}


34

DictionariesmonthsDictionary = { 1 : "January", 2 : "February", 3 : "March", 4 : "April", 5 : "May", 6 : "June", 7 : "July", 8 : "August", 9 : "September", 10 : "October", 11 : "November", 12 : "December" } print "The dictionary items are:"print monthsDictionary.items() print "\nThe dictionary keys are:"print monthsDictionary.keys() print "\nThe dictionary values are:"print monthsDictionary.values() print "\nUsing a for loop to get dictionary items:" for key in monthsDictionary.keys(): print "monthsDictionary[", key, "] =", monthsDictionary[ key ]

Creates a dictionary with the month number as the key and the month name as the value

Prints out all the items, both key and value, in the dictionary

Prints out all the keys in the dictionary

Prints out just the values in the dictionary

Loops though using the keys to display all the items in the dictionary


35

DictionariesThe dictionary items are:[(1, 'January'), (2, 'February'), (3, 'March'), (4, 'April'), (5, 'May'), (6, 'June'), (7, 'July'), (8, 'August'), (9, 'September'), (10,

'October'), (11, 'November'), (12, 'December')] The dictionary keys are:[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] The dictionary values are:['January', 'February', 'March', 'April', 'May', 'June', 'July', 'August', 'September', 'October', 'November', 'December'] Using a for loop to get dictionary items:monthsDictionary[ 1 ] = JanuarymonthsDictionary[ 2 ] = FebruarymonthsDictionary[ 3 ] = MarchmonthsDictionary[ 4 ] = AprilmonthsDictionary[ 5 ] = MaymonthsDictionary[ 6 ] = JunemonthsDictionary[ 7 ] = JulymonthsDictionary[ 8 ] = AugustmonthsDictionary[ 9 ] = SeptembermonthsDictionary[ 10 ] = OctobermonthsDictionary[ 11 ] = NovembermonthsDictionary[ 12 ] = December


36

Hangman Program Again

• Example: Hangman

http://www.cs.kent.edu/~mscherge/ICP/PythonBookExamples/chap05/hangman.py

October 17, 2005ICP: Chapter 5: Lists and Dictionaries 1 Introduction to Computer Programming...

Documents

Transcript of October 17, 2005ICP: Chapter 5: Lists and Dictionaries 1 Introduction to Computer Programming...